@inproceedings{pytorch,
      title = {{PyTorch: An Imperative Style, High-Performance Deep Learning Library}},
     author = {Paszke, Adam and Gross, Sam and Massa, Francisco and Lerer, Adam and Bradbury, James and Chanan, Gregory and Killeen, Trevor and Lin, Zeming and Gimelshein, Natalia and Antiga, Luca and Desmaison, Alban and Kopf, Andreas and Yang, Edward and DeVito, Zachary and Raison, Martin and Tejani, Alykhan and Chilamkurthy, Sasank and Steiner, Benoit and Fang, Lu and Bai, Junjie and Chintala, Soumith},
     editor = {H. Wallach and H. Larochelle and A. Beygelzimer and F. d\textquotesingle Alch\'{e}-Buc and E. Fox and R. Garnett},
  booktitle = {{Advances in Neural Information Processing Systems}},
   location = {{Vancouver, BC, Canada}},
  articleno = {721},
   numpages = {12},
     volume = {32},
      pages = {8024--8035},
       year = {2019},
  publisher = {{Curran Associates, Inc.}},
    address = {{Red Hook, NY, USA}}
}
@article{torch_ecg_paper,
      title = {{A Novel Deep Learning Package for Electrocardiography Research}},
     author = {Hao Wen and Jingsu Kang},
    journal = {{Physiological Measurement}},
        doi = {10.1088/1361-6579/ac9451},
       year = {2022},
      month = {11},
  publisher = {{IOP Publishing}},
     volume = {43},
     number = {11},
      pages = {115006}
}
@article{Kang_2022_cinc2021_iop,
      title = {{A Study on Several Critical Problems on Arrhythmia Detection using Varying-Dimensional Electrocardiography}},
     author = {Jingsu Kang and Hao Wen},
    journal = {{Physiological Measurement}},
        doi = {10.1088/1361-6579/ac6aa3},
       year = {2022},
      month = {6},
  publisher = {{IOP Publishing}},
     volume = {43},
     number = {6},
      pages = {064007}
}
@inproceedings{resnet,
      title = {{Deep Residual Learning for Image Recognition}},
     author = {He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
  booktitle = {{2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}},
      pages = {770--778},
       year = {2016},
      month = {6},
  publisher = {{Institute of Electrical and Electronics Engineers (IEEE)}},
        doi = {10.1109/cvpr.2016.90}
}
@article{awni2019stanford_ecg,
      title = {{Cardiologist-Level Arrhythmia Detection and Classification in Ambulatory Electrocardiograms using a Deep Neural Network}},
     author = {Hannun, Awni Y and Rajpurkar, Pranav and Haghpanahi, Masoumeh and Tison, Geoffrey H and Bourn, Codie and Turakhia, Mintu P and Ng, Andrew Y},
    journal = {{Nature Medicine}},
        doi = {10.1038/s41591-018-0268-3},
       year = {2019},
      month = {1},
  publisher = {{Springer Science and Business Media LLC}},
     volume = {25},
     number = {1},
      pages = {65--69}
}
@article{cai2020rpeak_seq_lab_net,
      title = {{QRS Complex Detection using Novel Deep Learning Neural Networks}},
     author = {Cai, Wenjie and Hu, Danqin},
    journal = {{IEEE Access}},
     volume = {8},
        doi = {10.1109/access.2020.2997473},
      pages = {97082--97089},
       year = {2020},
  publisher = {{Institute of Electrical and Electronics Engineers (IEEE)}}
}
@book{zhang2023dive,
      title = {{Dive into Deep Learning}},
     author = {Zhang, Aston and Lipton, Zachary C. and Li, Mu and Smola, Alexander J.},
  publisher = {{Cambridge University Press}},
       note = {\url{https://d2l.ai}},
       year = {2023}
}
@article{dumoulin2016guide,
    title = {{A Guide to Convolution Arithmetic for Deep Learning}},
   author = {Dumoulin, Vincent and Visin, Francesco},
  journal = {{ArXiv e-prints}},
   eprint = {1603.07285},
     year = {2016},
    month = {3},
      doi = {10.48550/ARXIV.1603.07285}
}
@article{chen2017_deeplabv3,
    title = {{Rethinking Atrous Convolution for Semantic Image Segmentation}},
   author = {Liang-Chieh Chen and George Papandreou and Florian Schroff and Hartwig Adam},
  journal = {arXiv preprint arXiv:1706.05587v3},
     year = {2017},
    month = {6},
      doi = {10.48550/ARXIV.1706.05587},
}
@inproceedings{yun2019cutmix,
      title = {{CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features}},
     author = {Yun, Sangdoo and Han, Dongyoon and Oh, Seong Joon and Chun, Sanghyuk and Choe, Junsuk and Yoo, Youngjoon},
  booktitle = {{Proceedings of the IEEE/CVF International Conference on Computer Vision}},
      pages = {6022--6031},
       year = {2019},
      month = {10},
        doi = {10.1109/ICCV.2019.00612},
  publisher = {{Institute of Electrical and Electronics Engineers (IEEE)}},
   location = {{Seoul, Korea (South)}}
}
@inproceedings{yao2018ti_cnn,
      title = {{Time-Incremental Convolutional Neural Network for Arrhythmia Detection in Varied-Length Electrocardiogram}},
     author = {Yao, Qihang and Fan, Xiaomao and Cai, Yunpeng and Wang, Ruxin and Yin, Liyan and Li, Ye},
  booktitle = {{2018 IEEE 16th Intl Conf on Dependable, Autonomic and Secure Computing, 16th Intl Conf on Pervasive Intelligence and Computing, 4th Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress (DASC/PiCom/DataCom/CyberSciTech)}},
      pages = {754--761},
       year = {2018},
      month = {8},
        doi = {10.1109/dasc/picom/datacom/cyberscitec.2018.00131},
  publisher = {{Institute of Electrical and Electronics Engineers (IEEE)}},
   location = {{Athens, Greece}}
}
@article{yao2020ati_cnn,
      title = {{Multi-Class Arrhythmia Detection from 12-Lead Varied-Length ECG using Attention-Based Time-Incremental Convolutional Neural Network}},
     author = {Yao, Qihang and Wang, Ruxin and Fan, Xiaomao and Liu, Jikui and Li, Ye},
    journal = {{Information Fusion}},
        doi = {10.1016/j.inffus.2019.06.024},
     volume = {53},
      pages = {174--182},
       year = {2020},
      month = {1},
  publisher = {{Elsevier}}
}
@article{faust2018automated,
      title = {{Automated Detection of Atrial Fibrillation using Long Short-Term Memory Network with RR Interval Signals}},
     author = {Faust, Oliver and Shenfield, Alex and Kareem, Murtadha and San, Tan Ru and Fujita, Hamido and Acharya, U Rajendra},
    journal = {{Computers in Biology and Medicine}},
     volume = {102},
      pages = {327--335},
        doi = {10.1016/j.compbiomed.2018.07.001},
       year = {2018},
      month = {11},
  publisher = {{Elsevier}}
}
@article{af_detection,
       title = {{A Scalable Hybrid Model for Atrial Fibrillation Detection}},
      author = {Hao Wen and Wenjian Yu and Yuanqing Wu and Shuai Yang and Xiaolong Liu},
     journal = {{Journal of Mechanics in Medicine and Biology}},
         doi = {10.1142/s0219519421400212},
        year = {2021},
       month = {4},
   publisher = {{World Scientific Pub. Co. Pte. Lt.}},
      volume = {21},
      number = {05},
       pages = {2140021}
}
@incollection{moskalenko2019deep,
      title = {{Deep Learning for ECG Segmentation}},
     author = {Viktor Moskalenko and Nikolai Zolotykh and Grigory Osipov},
  booktitle = {{Studies in Computational Intelligence}},
        doi = {10.1007/978-3-030-30425-6_29},
       year = {2019},
      month = {9},
  publisher = {{Springer International Publishing}},
      pages = {246--254}
}
@inproceedings{densenet,
      title = {{Densely Connected Convolutional Networks}},
     author = {Huang, Gao and Liu, Zhuang and Van Der Maaten, Laurens and Weinberger, Kilian Q},
  booktitle = {{Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition}},
        doi = {10.1109/cvpr.2017.243},
      pages = {2261-2269},
       year = {2017},
      month = {7},
  publisher = {{Institute of Electrical and Electronics Engineers (IEEE)}}
}
@article{huang2022densenet2,
      title = {{Convolutional Networks with Dense Connectivity}},
     author = {Gao Huang and Zhuang Liu and Geoff Pleiss and Laurens van der Maaten and Kilian Q. Weinberger},
    journal = {{IEEE Transactions on Pattern Analysis and Machine Intelligence}},
        doi = {10.1109/tpami.2019.2918284},
       year = {2022},
      month = {12},
  publisher = {{Institute of Electrical and Electronics Engineers (IEEE)}},
     volume = {44},
     number = {12},
      pages = {8704--8716}
}
@article{howard2017mobilenets,
    title = {{MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications}},
   author = {Howard, Andrew G and Zhu, Menglong and Chen, Bo and Kalenichenko, Dmitry and Wang, Weijun and Weyand, Tobias and Andreetto, Marco and Adam, Hartwig},
  journal = {{arXiv preprint arXiv:1704.04861}},
     year = {2017},
      doi = {10.48550/ARXIV.1704.04861}
}
@inproceedings{sandler2018mobilenetv2,
      title = {{MobileNetV2: Inverted Residuals and Linear Bottlenecks}},
     author = {Mark Sandler and Andrew Howard and Menglong Zhu and Andrey Zhmoginov and Liang-Chieh Chen},
  booktitle = {{2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition}},
        doi = {10.1109/cvpr.2018.00474},
       year = {2018},
      month = {6},
      pages = {4510-4520},
   location = {{Salt Lake City, UT, USA}},
  publisher = {{Institute of Electrical and Electronics Engineers (IEEE)}}
}
@inproceedings{howard2019mobilenetv3,
      title = {{Searching for MobileNetV3}},
     author = {Andrew Howard and Mark Sandler and Bo Chen and Weijun Wang and Liang-Chieh Chen and Mingxing Tan and Grace Chu and Vijay Vasudevan and Yukun Zhu and Ruoming Pang and Hartwig Adam and Quoc Le},
  booktitle = {{2019 IEEE/CVF International Conference on Computer Vision (ICCV)}},
        doi = {10.1109/iccv.2019.00140},
       year = {2019},
      month = {10},
  publisher = {{Institute of Electrical and Electronics Engineers (IEEE)}}
}
@inproceedings{chollet2017xception,
      title = {{Xception: Deep Learning with Depthwise Separable Convolutions}},
     author = {Chollet, Fran{\c{c}}ois},
  booktitle = {{Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition}},
      pages = {1251--1258},
        doi = {10.1109/cvpr.2017.195},
       year = {2017},
      month = {7},
}
@inproceedings{unet,
         title = {{U-Net: Convolutional Networks for Biomedical Image Segmentation}},
        author = {Ronneberger, Olaf and Fischer, Philipp and Brox, Thomas},
     booktitle = {{International Conference on Medical Image Computing and Computer Assisted Intervention}},
         pages = {234--241},
          year = {2015},
  organization = {Springer}
}
@article{kaiser2017separable_conv,
    title = {{Depthwise Separable Convolutions for Neural Machine Translation}},
   author = {Kaiser, Lukasz and Gomez, Aidan N and Chollet, Francois},
  journal = {{arXiv preprint arXiv:1706.03059}},
     year = {2017},
      doi = {10.48550/ARXIV.1706.03059}
}
@inproceedings{kaiser2018separable_conv,
      title = {{Depthwise Separable Convolutions for Neural Machine Translation}},
     author = {Lukasz Kaiser and Aidan N. Gomez and Francois Chollet},
  booktitle = {{International Conference on Learning Representations}},
       year = {2018},
        URL = {https://openreview.net/forum?id=S1jBcueAb},
}
@misc{gomez2020separable_conv_patent,
      title = {{Depthwise Separable Convolutions for Neural Machine Translation}},
     author = {Gomez, Aidan Nicholas and Kaiser, Lukasz Mieczyslaw and Chollet, Francois},
       year = {2020},
      month = {12},
  publisher = {Google Patents},
       note = {{US Patent 10,853,590}}
}
@inproceedings{zhang2019blur_pool,
         title = {{Making Convolutional Networks Shift-Invariant Again}},
        author = {Zhang, Richard},
     booktitle = {{International Conference on Machine Learning}},
         pages = {7324--7334},
          year = {2019},
  organization = {{PMLR}}
}
@inproceedings{wang2018non_local_net,
      title = {{Non-Local Neural Networks}},
     author = {Wang, Xiaolong and Girshick, Ross and Gupta, Abhinav and He, Kaiming},
  booktitle = {{2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}},
      pages = {7794--7803},
        doi = {10.1109/cvpr.2018.00813},
       year = {2018},
      month = {6},
   location = {{Salt Lake City, UT, USA}},
  publisher = {{IEEE}}
}
@article{hu2020senet,
     title = {{Squeeze-and-Excitation Networks}},
    author = {Jie Hu and Li Shen and Samuel Albanie and Gang Sun and Enhua Wu},
   journal = {{IEEE Transactions on Pattern Analysis and Machine Intelligence}},
      year = {2020},
    volume = {42},
    number = {8},
     pages = {2011-2023},
 publisher = {{Institute of Electrical and Electronics Engineers (IEEE)}},
       doi = {10.1109/tpami.2019.2913372}
}
@inproceedings{hu2018senet,
      title = {{Squeeze-and-Excitation Networks}},
     author = {Jie Hu and Li Shen and Gang Sun},
  booktitle = {{2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}},
        doi = {10.1109/cvpr.2018.00745},
       year = {2018},
      month = {6},
      pages = {7132-7141},
  publisher = {{IEEE}},
   location = {{Salt Lake City, UT, USA}}
}
@inproceedings{li2019sknet,
      title = {{Selective Kernel Networks}},
     author = {Li, Xiang and Wang, Wenhai and Hu, Xiaolin and Yang, Jian},
  booktitle = {{2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}},
      pages = {510--519},
        doi = {10.1109/cvpr.2019.00060},
       year = {2019},
      month = {6},
  publisher = {{IEEE}},
   location = {{Long Beach, CA, USA}}
}
@inproceedings{cao2019GCNet,
      title = {{GCNet: Non-Local Networks Meet Squeeze-Excitation Networks and Beyond}},
     author = {Cao, Yue and Xu, Jiarui and Lin, Stephen and Wei, Fangyun and Hu, Han},
  booktitle = {{2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)}},
       year = {2019},
      month = {10},
      pages = {1971-1980},
        doi = {10.1109/ICCVW.2019.00246}
}
